Data analysis using SQL and Excel
Data Analysis Using SQL and Excel, 2nd Edition shows you how to leverage the two most popular tools for data query and analysis-SQL and Excel-to perform sophisticated data analysis without the need for complex and expensive data mining tools. Written by a leading expert on business data mining, this...
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| Main Author: | |
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| Format: | Book |
| Language: | English |
| Published: |
Indianapolis, IN
Wiley
[2016]
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| Edition: | Second edition |
| Subjects: | |
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| 100 | 1 | |a Linoff, Gordon |e author | |
| 245 | 1 | 0 | |a Data analysis using SQL and Excel |c Gordon S. Linoff |
| 250 | |a Second edition | ||
| 264 | 1 | |a Indianapolis, IN |b Wiley |c [2016] | |
| 264 | 4 | |c ©2016 | |
| 300 | |a xlvi, 744 pages |b illustrations |c 24 cm | ||
| 336 | |a text |2 rdacontent | ||
| 337 | |a unmediated |2 rdamedia | ||
| 338 | |a volume |2 rdacarrier | ||
| 500 | |a Includes index | ||
| 520 | |a Data Analysis Using SQL and Excel, 2nd Edition shows you how to leverage the two most popular tools for data query and analysis-SQL and Excel-to perform sophisticated data analysis without the need for complex and expensive data mining tools. Written by a leading expert on business data mining, this book shows you how to extract useful business information from relational databases. You'll learn the fundamental techniques before moving into the "where" and "why" of each analysis, and then learn how to design and perform these analyses using SQL and Excel. Examples include SQL and Excel code, and the appendix shows how non-standard constructs are implemented in other major databases, including Oracle and IBM DB2/UDB. The companion website includes datasets and Excel spreadsheets, and the book provides hints, warnings, and technical asides to help you every step of the way. | ||
| 592 | |a 00101/HL/2019 (750) |b 27/9/9/19 |c RM224.68 |h Han Lin Books | ||
| 630 | 0 | 0 | |a Microsoft Excel (Computer file) |
| 650 | 0 | |a SQL (Computer program language) | |
| 650 | 0 | |a Querying (Computer science) | |
| 650 | 0 | |a Data mining | |
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